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Nature's Design's: The Biology of Survival

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Nature's Design's: The Biology of Survival
Pam Mantri1*, John Thomas1
1Cognitive Tools Ltd. LLC, P.O. Box 695; 255 North Ave; New Rochelle, NY 10801, USA
Abstract. Life has existed on earth for at least 3.95 billion years. All along, the flame of life has been successfully
passed on from generation to generation, and species to species across an immense temporal span. This includes at
least five mass-extinction events that wiped out over 70% of all species in each such biotic crisis. Against such
immense odds, life has learned to thrive despite repeat assaults. And the ingenuity embedded within natures designs
has been an integral part of this inspiring story. For example, the ancient bacterial flagellum is powered by the Mot
Complex which is part of a perfectly circular nanoscale rotary engine. It is obvious that nature came upon the wheel
much before human arrival (i.e., at least as far back as 2.7 billion years). Many are the design lessons that may be
gleaned from studying nature. This paper looks at the immense evolutionary design-laboratory that nature evolves its
designs within, and frames it alongside an Axiomatic/Complex-Adaptive/Stigmergic Systems perspective.
Keywords: Axiomatic Design; Biological Systems; Stigmergy; Emergence; Complex Adaptive System; Evolution.
1 Introduction
Form and function are discernable across the biological
order; for example, form in anatomy and its
corresponding function in physiology. Unfortunately,
research in the world of modern biology is currently
divorced from that of design-theory. Yet each discipline
could benefit from studying the other. From a design
perspective (and subject to environment/precedent
constraints), form seems to be following function (e.g.,
the elbow joint of the fore-arm for bringing food to the
mouth). The fundamental problem associated with design
in biology, is that of agency. Thus, while the act of design
implies a purposeful designer, biological “designs”
operate bereft of such agency, and therefore explicit
intent. If no designer is standing by the biological artifact
in question; if there are no design documents in the
biological archives, how could the intention of function
be properly inferred and ascribed? In this paper, we try to
bridge the seemingly insurmountable gap between design-
theory and biological “designs,” without getting derailed
by “intelligent design” polemics.
In Section 2, we establish the stigmergic teleology for
biological designs. This helps bring biological designs
into the normal design discourse. Section 3 discusses the
organic/biological genesis of the design motto form
follows function,” and its linkages to the axiomatic
framework. In Section 4, the design of the bacterial
flagellum which compotes well with the axiomatic
framework has been captured. Section 5 discusses the
dynamics of evolution from a design matrix perspective.
2 Stigmergic Teleology of Biology
As Prof. Dawkins asserts in [1]:
The total amount of suffering per year in the
natural world is beyond all decent contemplation.
During the minute that it takes me to compose this
sentence, thousands of animals are being eaten
alive, many others are running for their lives,
whimpering with fear, others are slowly being
devoured from within by rasping parasites,
thousands of all kinds are dying of starvation, thirst,
and disease....The universe that we observe has
precisely the properties we should expect if there is,
at bottom, no design, no purpose, no evil, no good,
nothing but pitiless indifference. (Emphasis added.)
It was Darwin who first made known the ordering
principle of natural selection in biology [2]:
One general law, leading to the advancement of
all organic beings, namely, multiply, vary, let the
strongest live and the weakest die.
Yet Darwin was acutely aware of the absurdity of the
designerly lacuna [2]:
To suppose that the eye with all its inimitable
contrivances for adjusting the focus to different
distances, for admitting different amounts of light,
and for the correction of spherical and chromatic
aberration, could have been formed by natural
selection, seems, I confess, absurd in the highest
degree. When it was first said that the sun stood
still and the world turned round, the common sense
of mankind declared the doctrine false; but the old
saying of Vox populi, vox Dei, as every philosopher
knows, cannot be trusted in science....The difficulty
of believing that a perfect and complex eye could
be formed by natural selection, though insuperable
by our imagination, should not be considered
subversive of the theory.
It is not that Darwin did not believe his theory; on the
contrary, he was quite willing to oppose the common
sense (i.e., "Vox populi, vox Dei") of his time. Yet there
is something unsatisfactory about how function and form
(i.e., design) come together without any role for the
If a top-down role is problematic, is it perhaps possible
to establish a bottom-up, boot-strapping role for design?
Four supportive concepts [3] (Stigmergy, Complex
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Adaptive Systems, Knowledge Hierarchies &
Emergence) need to be briefly reviewed to help shift the
problem of biological design into a bottom-up approach.
Fig. 1. Stigmergic trails (using NetLogo [4])
Stigmergy [5] denotes call to work based on local signs
or markings (such as the ant trail in the adjacent Fig. 1)
leftbybiologicalagents(α)atsometimeinthepast and
during the course of their work (either as a side-effect of
the said work or as something in addition to the work).
These markings aggregate to provide organizational
directives(β-logic) available at various levels, both within
the environment as well as within and between agents.
Thus, even though there is no one controlling the set of
agents in a top-down sense, there is nevertheless system-
wide control being established in a bottom-up sense.
Fig. 2. Complex Adaptive System: Basic vs. Iterative (Reproduced with Permission [3])
Stigmergic ordering is well established across all
scales (micro-meso-macro) of biological systems. For
example,thepheromonemarkingsthatanagent ant (αi)
leaves behind as it navigates an unknown terrain helps it
to navigate back home instead of being lost (with near-
certain death as its fate). And if perchance, it does chance
upon a choice food item, these same pheromone patterns
(βj)helprallyotherantagentstojointlyhaulthefood back
to the nest. While biological in origin, the pheromone
droppings are not alive. Yet in aggregate, these markings
help organize a swarm of ants in a purposeful pursuit. The
ants themselves need not be aware of the bigger picture;
all that is required is that certain chance mutations have
enabled a certain species to be the first in secreting the
pheromone droppings. And from then on, the Darwinian
survival of the fittest would give it reproductive
Stigmergic ordering helps biological systems evolve
and adapt to form higher levels of complexity under the
rubric of Complex Adaptive System’s (CAS) and
Complex Adaptive System of Systems (CASoS). As Prof.
Holland describes it [6],CAS’s“are systems that have a
large number of components, often called agents that
interact and adapt or learn.” Holland then proposed a
two-tiered system as shown in Fig. 2a above. The lower
α-tier follows a fast-dynamic and is engaged in the flow of
resources between diverse agents while the upperβ-tier
follows a slow-dynamic that captures stigmergic artifacts
and aggregates from these which are then emitted system-
wide as stigmergic signals that help the agents organize
and scale.
Fig. 3. Knowledge Hierarchy/Interdisciplinary Heterarchy
(Reproduced with Permission [3])
When considering the production of knowledge corpus,
humans may also be considered as stigmergic agents. The
knowledge that we create helps organize human activities
in myriad ways beyond the original intent. In other words,
the production of human knowledge (as a β-tier
aggregate) is itself a CAS process [3]. The form of human
knowledge has a conical structure to it; i.e., by the very
nature of abstractions, there are many more concretes than
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abstractions. Likewise, there are many more abstractions
versus abstraction-of-abstractions. Such pyramidic
structuring results from our cognitive need to reduce the
complexity of whatever we are dealing with into
something manageable. For example, Occam’s razor
(which asserts that one should not make more
assumptions than the minimum needed) is an example of
such a cognitive need. The end result is that human
knowledge has a pyramidic structure as shown in Fig. 3b
above. Here, the inductive arch is the upward flowing
trace that is involved in creating higher-level
generalizations. In contrast, a deduction is the downward
flowing trace involved in the application of the induced
generalizations. But human knowledge is not the output
of any one agent; it instead captures the sum-total of such
population-wide outpourings that are painstakingly
curated and accumulated across time. And when multiple
domains are mapped side-by-side along with their shared
conceptual linkages, the various hierarchies map onto a
heterarchical span (Fig. 3c) that share and cross-pollinate
across the domain barriers. Fig. 3a captures the rate of
change across the hierarchy.
Fig. 4. Ontological vs. Epistemological Emergence
(Reproduced with Permission [3])
Now consider the problem of emergence.
Reductionism (i.e., whole is the sum of its parts), attempts
to reduce all existents to a minimal set. In contrast,
emergentism (i.e., the whole is more than the sum of its
parts), tracks systemic properties that evaded the
reductionist capture. Fundamental existents and concepts
in biology (such as life, consciousness, etc.) pertain to
emergent properties.
Ontology is the study of entities that exist.
Epistemology is the meta-level study of our knowledge of
those entities. As shown in [3], emergence may be
considered either ontologically or epistemologically (Fig.
4). Ontological emergence is irreducible to its constituent
parts; for example, the phenomenon of life is irreducible
to its ultimate physical constituents. Ontologically, life is
thus a novel property irreducible to its physical
constituents regardless of the state of our knowledge
about it. In contrast, an epistemologically emergent
awareness is a novel concept that is not reducible to our
knowledge of the constituent parts; i.e., it needs
overarching emergent concepts rendered as white dots in
panel-EI/Fig. 4. The panels are marked with the leading
letters of the intersecting coordinates; for example, ER
denotes epistemologically-reducible. EI may be
associated with OR, for example in making sense of the
rainbow in ancient times (e.g., bow for the warrior gods).
There can also be erroneous EI without the corresponding
OI (for example, the four humors in ancient holistic
medicine as well as the error of the afore-mentioned
“intelligent design”). Most often, our awareness of OI
precedes our theorizing about it and thus formulating a
corresponding EI. Many of the emergent properties (such
as life and consciousness) are currently in the state of OI
without having advanced to the state of EI yet.
Having briefly reviewed the four requisite themes
(i.e., Stigmergy, CAS, Knowledge Hierarchies &
Emergence), we are now in a position to consider the
challenge of bottom-up teleology in biological systems.
Historically, the field of teleology was established by
Aristotle for studying final-causation (which roughly
translates to function). Humans are paradigm examples of
this view as they are self-conscious and sufficiently self-
aware to recognize internal intentions that may be
vocalized and probed. This view was then
anthropomorphically extended to include the behavior of
animals and plants. Each such extension required
loosening the anthropomorphic strings to include lower-
level conscious, and vegetative actions [7]. But in each of
these cases, the teleological intent is invested at the agent
level, and not across a collection of agents. We need
stigmergic teleology to help us step beyond the agent
Consider once again, the ant-trail across a soil track.
Soil, stand-alone is not teleological. But when a critical
mass of ants (in search of food), embed their pheromone
droppings in the soil-bed, it then becomes imbued with
teleological directiveness to help the ant-colony
successfully scavenge for food. A stand-alone Robinson-
Crusoe ant could not have triggered such a collective
endeavor; for the pheromone trail would have evaporated
and vanished in due course. Also, just a few ants could
not have sustained the trail as it would have likewise
vanished. Instead, it required a critical mass of ants to
constantly replenish the evaporating pheromone scent
markings. In other words, the stigmergic goal did not
precipitate at the αi, stand-alone ant level; it instead
required a critical mass of ant agents that needed guidance
across many αi-βj cue-and-response cycles. It is at this
critical tipping-point that the ant-trail (along with its
marching ants) may be said to be teleologically invested.
Thus, given the problem context of the ant-trail (as a
means for path-finding for food), it is precisely this
critical mass of ants as a unit that is minimally and
independently teleologically invested.
Stigmergic teleology works across all scales,
including the micro-level. For example, Tabony reports
the existence of molecular level stigmergic mechanisms
within the cell-biology of the tubulin protein [8]:
…they self-organize and develop other higher-level
emergent phenomena by a process where individual
micro-tubules are coupled together by the chemical
trails they produce by their own reactive growing and
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β-level stigmergic markings are not restricted to happen
in the environment (i.e., pheromone excretions into the
soil for the ant-trail); it could also be entrapped within the
agent as DNA messaging and shared either vertically (i.e.,
genetic reproduction to create new agents) or laterally
(transformation, transduction, and conjugation) between
existing agents.
All design involves searches through massive design
spaces. Using lateral gene transfer, bacterial colonies are
able to evolve antibiotic resistance at a rapid pace. Even
though bottom-up stigmergic design is non-conceptual, it
is immensely efficient in scale and scope. Imagine if the
underlying stigmergic design patterns & principles were
to be rendered conceptually legible?
Stigmergic teleology is a bottom-up emergence of
function at theβ-level that helps guide and orchestrate the
coveredagentactivitiesattheα-level. Also, it is bottom-
up stigmergic teleology that could have helped Darwin
overcome the aforementioned absurdity of the top-down
designerly lacuna.
3. Biology of Form Follows Function
It was architect Louis Sullivan (father of the iconic
skyscraper design, and mentor to Frank Lloyd Wright)
who first coined the phrase "form follows function" in [9]:
Whether it be the sweeping eagle in his flight, or
the open apple-blossom, the toiling work-horse, the
blithe swan, the branching oak, the winding stream
at its base, the drifting clouds, over all the coursing
sun, form ever follows function, and this is the law.
Where function does not change, form does not
change...It is the pervading law of all things organic
and inorganic, of all things physical and
metaphysical, of all things human and all things
superhuman, of all true manifestations of the head, of
the heart, of the soul, that the life is recognizable in
its expression, that form ever follows function. This is
the law.
In the above origination of the pithy formulation,
Sullivan has an expansive inclusiveness to the concept of
form. By form, he doesn't merely mean the shape or
configuration of something; instead, it is the existential
manifestation of a thing in all its "physical and
metaphysical" properties. In the world of design, these are
the design-parameters (i.e., DP's) that the designer is
trying to assemble and configure. In other words, "form
follows function" is indeed the familiar mapping between
Design Parameters (DP’s) and Functional Requirements
(FR’s) in the axiomatic world. Depending on the scale at
which the design is operating (micro-meso-macro),
biological forms may range from quantum mechanics (that
underlies photo-synthesis), molecular biology of the cell
(that underlies DNA replication), physics of the cellular
transport (such as the Mot Complex), anatomy of the
organ and tissue systems (such as respiratory, digestive),
In all of these manifestations, since there are no agent-
designers available for interrogation about the governing
functions at large, all the hiddenFR↔DPmappingsneed
to be induced and reverse-engineered to help understand
the operative principles of stigmergic designs that are
available in nature.
In the quest for survival against immense odds,
biological agents have been instruments of stigmergic
design across vast temporal expanses. Or as recounted in
Trapped within the sparse coils of the DNA (which
consists of about 1.5 GB of DVD-sized data), one may
witness the essence of the Information Axiom
operating in a self-organizing context. Herein, the
genetic code orchestrates the embryonic self-
articulation and development of a complex living
entity (consisting of about 150 zettabytes of data and
requiring about 30 Manhattan-size datacenters to
merely store) that can struggle, adapt and thrive in
heretofore novel and unknown environments with
ever changing risks and opportunities.
4. Bacterial Flagellum Design
The flagellum is for sensing, orienting, and locomotion
of cells of organisms in low Reynolds number (high
viscosity relative to mass) media. Flagellum is Latin for a
whip. Flagella are found on all three main branches of the
evolutionary tree: prokaryotes (e.g., E. coli), archae (e.g.,
Methanococcus voltae) and eukaryotes (e.g., sperm).
Prokaryotes use rotary movement at the flagellar base for
propulsion. In other words, the wheel that is embedded in
the motor was invented by nature much before human
arrivaland at least as far back as 2.7 billion years.
For a bacterium that is around 2-3 microns in length, its
flagella are about 1030 nm in diameter and 520μm in
length (Fig. 5a). The basic function of the flagellum is for
locomotion. The sensory organelle for a bacterium is the
array of methyl-accepting chemotaxis proteins (MCP’s)
embedded in the inner membrane. MCP’s are sensitive to
changes in the environment such as chemicals
(attractants/repellents), temperature, pH, etc. The protein
wheel structure of the nanoscale molecular rotary engine
has its (cell-membrane embedded) stator composed of the
Mot Complex (MotA/MotB). The rotor consists of 4
protein complexes (FliF, FliG, FliM, and FliN). The last
three of these also act as a molecular switch that enables
clockwise (CW) and counterclockwise (CCW) switching
based upon messaging signals from MCP. The stator-rotor
engine is powered by the Proton Motive Force (PMF)
pump that uses electrochemical potential difference to
build up a proton gradient across the inner cytoplasmic
membrane [11]. Stand-alone (i.e., without the attached
flagellum), the rotor can operate in the 20,000-100,000-
rpm range; with the attached flagellum, it reaches 200-
1000 rpm. As there is no ignition key for the flagellar
motor, it keeps rotating. Rotation is stopped using the
EpsE protein that attaches to the FliF-complex of the rotor
and acts as a clutch to stop the flagellum, resulting in a
stationary bacterium [12]. With femtoampere currents
being generated, the energy consumption is minuscule
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Fig. 5. The Flagellar Mot Complex vs. T3SS Injectisome (Adapted from Wikipedia [14,15])
("just one ten-quadrillionth of a watt" [13]). As Prof.
Namba recounts in [13]: “This structure is basically 100%
energy efficient. It is an extremely exquisite
Fig. 6. The Flagellar Mot Complex Design
The flagellar hook is a molecular universal joint.
Traditional universal joints have a center block that helps
transmit the rotary motion across axes that are inclined
with each other. The molecular flagellar hook is able to do
the same in far more degrees of axis inclination and with
no center block transfer mechanism. Instead, the
molecular sleeve of the hook reshapes and reorients itself
in a flexible manner.
The bacterial locomotion is a biased random walk.
Unlike a pure random walk that has uniform probabilities
in all possible degrees of freedom, a biased random walk
has non-uniform probabilities (i.e., biases) in certain
preferred directions. Thus, when the MCP on the
flagellum senses favorable environments in the direction
that it was moving in, it signals the CW/CCW switch in
the rotor to continue along CCW. However, when MCP
senses unfavorable environments in the direction that it
was moving in, it initiates the CW/CCW switch to reverse
into CW mode. This switch initiates the bacterial tumble
that results in a random change in the direction of
locomotion, but away from the non-favorable
With the above review of the main elements of the
flagellar system, the overall design can now be traced [16]
as shown in Fig. 6. The locomotion of the flagellated
bacterium may be observed in three distinct cases:
M: Motion towards attractants or away from
ML: Motionless state (such as when in a biofilm)
CD: Change-of-direction via tumbling
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The design leads with the sensory organelle MCP that
provides the discriminatory signal to the flagellar engine
to move towards an attractant, to move away from a
repellant, or to stay stationary in a satisfactory
environment. The PMF pump provides the motive energy
for the rotating elements. With the EpsE protein detached
from FliF, the rotating elements are engaged in the normal
CCW direction (Case M). In contrast, when EpsE is
attached to FliF, the rotating elements are disengaged
resulting in a stationary organism (Case ML). Whenever
the MCP proteins detect unfavorable conditions in the
direction of motion, it signals the basal elements of the
rotating flagellum (i.e., FliG, FliM, and FliN) to switch the
rotating direction from the default CCW to CW. This
triggers the random tumbling of the bacterium (Case CD).
During the process of tumbling, when the sensory
elements detect itself oriented in a favorable position, the
signal to switch to the default forward-propelling CCW is
sent. The hook (at the protruding base of the flagellum)
serves as a universal-joint for transmitting the torque. And
finally, the flagellum provides the propulsive thrust
against the low Reynolds medium.
Many of the functions and structures (and the
underlying proteins) observed in the bacterial flagellum
have also been found in the non-rotating Injectisome-
T3SS (Type Three Secretion System) used by bacteria in
injecting poisons such as the bubonic plague (bacterium
Yersinia Pestis) into a eukaryotic target (Fig. 5b). For
example, the hook is homologous between the flagellum
and the T3SS needle.
Three possibilities exist regarding the order of
evolution between Injectisome-T3SS and the flagellar
Bacterial flagellum preceded Injectisome-T3SS
Injectisome-T3SS preceded bacterial flagellum
Co-evolution of bacterial flagellum and
Injectisome-T3SS from a common ancestor
Current research has yet to conclude on the proper
evolutionary lineage. Nevertheless, it is important to
understand the evolutionary dynamic pressures on the
underlying design matrix. In the following section, we
look at the evolutionary dynamic of the FR↔DPDesign
5. Design Matrix Dynamics & Evolution
From recent evidence of microbial by-products found
in rocks from north-eastern Canada, it is now clear that life
has existed for at least 3.95 billion years [17]. The last 500
million years have witnessed five major mass extinction
events that wiped out over 70% of all species in each such
biotic crisis (Fig. 7).
The causes for the mass extinctions are varied and
include massive volcanic basalt-flood events, asteroid
strikes, sea-level changes, changes in the atmospheric gas
concentrations, etc. While 70% of life may have gone
extinct, the remaining 30% has learned to thrive despite
repeat assaults. And the ingenuity of the design potential
embedded within natures evolutionary mechanism has
been an integral part of this inspiring story.
Fig. 7. Big 5 Mass-Extinction Events (Adapted from [18, 19])
In any given ecosystem, there could be environmental
(e) changes in the habitat as well as evolutionary changes
within competing/collaborative (c) agents. In general,
there could be nine change categories between these two
factors (see Fig. 8 below with attached explanatory
Fig. 8. Nine Types of Selection Pressures
A few select examples to illustrate the above include:
c0e+/c0e-: An example of the environmental
selection pressure could be an ice-age type of climate
change into snowy, white-out conditions. In this
case, c0e+ selection pressure would favor animals of
a lighter colored coat to camouflage itself and survive
in the white-out climate better. Likewise, c0e- would
put selection pressure on animals with a darker coat
to evolve into a lighter shade.
c-e0/c+e0: The ongoing predator/prey arms-race
between the rough-skinned Newt (Taricha
Granulosa) and the Garter snake (Thamnophis
Sirtalis Parietalis) would illustrate the c-e0/c+e0
selection-pressure dynamic. The Newt produces
enough tetrodotoxin to kill several adult humans. But
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it is safe to handle the Newt as the toxin is safely
stored underneath the skin. The Garter snake preys on
the poisonous Newt and has to successfully digest the
toxic load. In evolutionary time-scales, the
competitive advantage has shifted back and forth
between these two antagonists. Currently, the
competitive advantage resides with the Garter snake
(i.e., it is, therefore, c+e0) while the Newt (c-e0) has
to evolve and store an even more potent tetrodotoxin
load beneath its skin [20].
c-e-/c+e+: About 200 of the 12,000 ant species that
exist today are of the invasive kind. By hitch-hiking
alongside human global travel patterns, these
invasive ant species have triggered dramatic bio-
diversity losses with concomitant economic damage.
Invasive species in the US alone cost an estimated
$138 billion/year [21]. An example of the non-
invasive species is L. Paralienus that is local to
Central Europe (including Austria, Bosnia, France,
Germany, Italy, Spain, Sweden, Switzerland, Turkey,
etc.). In contrast the invasive species, L. Neglectus
was initially local in its native range near the Black
Sea; it is now found all across Europe. Being more
adaptable to the human built-environment, it is
successfully displacing the local species such as the
L. Paralienus. In this example, the L. Paralienus
species is facing c-e- selection pressures (both from
the urban/built environment as well as the highly
adaptable/aggressive invasive species such as L.
Neglectus). In contrast, the invasive L. Neglectus
species is facing c+e+ selection pressures (given its
higher urban adaptability, its inherent aggressiveness
as well as favorable migratory pathways).
c0e0: In 1968, Biologist Motoo Kimura proposed the
neutral theory of molecular evolution [22]. It holds
that most changes at the molecular level occur from
the random genetic drift that does not compromise
existing functions and are therefore neutral with
respect to natural selection. c0e0 pertains to this
possibility. It is, however, possible that such a neutral
drift is not neutral (and therefore subject to
Darwinian selection) at a later stage when
circumstances have changed.
A fundamental question worth considering is to look at
how these evolutionary selection pressures impact the
design-matrix? In other words, what are the patterns of
design-matrix dynamics one should expect to see? For
example, where should one expect to see the primitive &
conserved genes, proteins, and functions to be more
favorably located on the design matrix? Likewise, where
should one expect the recent additions and deletions to be
located? Also, which areas of the design-matrix are more
vulnerable for a knockout. The following discussion uses
the design-matrix (Fig. 9) as a theoretical framework to
explore the evolutionary dynamics.
Fig. 9. Design Matrix & Evolutionary Dynamics
Imagine a decoupled legacy design with a 5x5 or a 6x6
design matrix as shown in Figs. 9a & 9e. The following
are some of the interesting design-matrix dynamics from
an evolutionary perspective:
new FR and its corresponding DP at the very top row
of the design matrix. Care is taken to make sure there
are no other spurious coupling terms associated with
this DP that compromise any other FR in the system.
With no coupling terms to compromise the existing
system, it is more than likely that such an addition
Figs.9a→9c: A singleton FR/DP addition could also
be made as any of the new rows without much
expense; it is effectively orthogonal to the existing
system. Likewise, if such a singleton FR/DP pair
currently exists in the legacy system, it would not
wreak havoc if it had to be knocked-out.
Figs.9a→9d:ThiscaseaddsanFR/DProw at the very
bottom along with full coupling with every other DP
that preceded and located above the new addition.
Such an addition would be minimally disruptive as it
can keep the legacy functions intact.
Figs.9e→9h:Thisistheknockoutcase which is the
reverse of the above case of Figs. 9a→9d.Andsimilar
to the above case, such a knockout would be minimally
disruptive as it can keep the remaining functions
Figs. 9e→9f & 9g: These are knockout cases (with
significant couplings) from the top & middle-zone
areas. Given that the couplings also need to be
knocked out, such deletions can be expensive.
MATEC Web of Conferences 301, 00023 (2019)
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There are many more similar transitions that the system
could be subjected to. But in broad terms, here are some
general patterns one could expect:
FR/DP pairs at the top of the design-matrix with
appropriate couplings (Fig. 9f) are likely to be more
primitive, not easily knocked-out and therefore, highly
Singleton FR/DP additions (Fig. 9b, 9c) could, in time,
come to serve as the origination point for new sub-
FR/DP pairs at the bottom of the design-matrix (even
with appropriate couplings) could be easily knocked-
out as well as added into the system without wrecking
system-wide havoc (Fig. 9d, 9h).
To illustrate the above dynamic, consider the central
dogma of molecular biology which highlights the
directionality of genetic information flow along the
first transcribed into various RNA components (i.e.,
mRNA, tRNA & rRNA). Once transcribed, the genetic
information is then translated into the requisite
polypeptides the cell needs. Located in the cytoplasm of
the cell, ribosomes are protein factories that help translate
the information contained within the mRNA into the
actual protein that the cell requires. Proteins are
constituted from a palette of 20 amino-acids. Casting the
above self-organization occurring within the cell in an
iterative-CAS framework (see section 2), if the amino-
acids are α1-level entities, information captured in the
RNA/DNA are β1/β2 patterns; and ribosomes are higher-
level α2+ entities. Higher the entity in the CAS
heterarchic-hierarchy, lower is the rate of change (similar
to Fig. 3.a). It is this differential rate of change that is
likely operative in the differential rates of genetic
conservation across evolutionary time-scales. For
example, consider the manufacture of the ribosome that
also needs to be periodically manufactured/replenished.
The requisite information for the manufacture of these
protein-factory ribosomes is transcribed into the rRNA
fragment (as mentioned above). The ribosome contains a
small subunit (SSU) as well as a large subunit (LSU).
Bacterial, archaeal as well as plastid SSU's are denoted
16S in reference to the centrifugal sedimentation rate
(Svedberg unit) they occupy. In contrast, eukaryotes such
as humans have their respective SSU in the 18S
sedimentation level. With this terminology in place, one
may recognize the significance of the highly-conserved
SSU component of the rRNA. Its conservation derives
from the ubiquitous role it plays in all protein synthesis
processes. Random mutations that compromise its
foundational protein-making function faces strong
selection pressures against it becoming prevalent. Even
so, SSU rRNA does suffer change. But that change is
occurring at such an infinitesimal pace that it helps trace
the very tree of life across evolutionary time-scales. Or
as Prof. Rogers indicates in [23]:
The SSU rRNA molecules are highly conserved, such
that bacterial ribosomal rRNA can be compared with
archaeal SSU rRNA and eukaryotic SSU rRNA. This
characteristic led Carl Woese and George Fox to
characterize the rRNA from a broad range of
organisms to form the first phylogenetic tree based
on molecular characters and led to finding an
entirely new taxon of life, the Archaea.
The SSU rRNA is an example of the FR/DP pairing that
is primitive, highly conserved and not easily knocked-out:
FR: Create gene-specific protein-making
DP: Ribosome as the custom, gene-specific,
protein-making factory.
Without the machinery for making proteins, the cell is
effectively dysfunctional. The SSU sRNA, therefore,
occupies the very top rungs of the design-matrix equation
(as shown in Fig. 9f). The SSU sRNA is one example of
the design-matrix based dynamic patterns that agree with
current research. But if this could be verified across an
ensemble of similar cases, such an approach could help
provide valuable guidance in allied domains such as
healthcare, animal care, farming, drug discovery, etc.
Axiomatic Design highlights the hierarchical structure
of design. As Prof. Suh highlights in two separate
instances in [16]:
Everything we do in design has a hierarchical
nature to it. That is, decisions must be made in
order of importance by decomposing the problem
into a hierarchy.... When such a hierarchical
nature of decision making is not utilized, the
process of decision making becomes very complex.
The designer must recognize and take advantage of
the existence of the functional and physical
hierarchies. A good designer can identify the most
important FRs at each level of the functional tree
by eliminating secondary factors from
consideration. Less-able designers often try to
consider all the FRs of every level simultaneously,
rather than making use of the hierarchical nature
of FRs and DP's.
these hierarchies may have significant value. But this
DP design complex. However, this needs to be
accomplished without the benefit of any closely aligned
prior art and its documentation. In reverse-engineering
any given product, the iterative, top-down, forward flow
between FRDP is reversed into an iterative, bottom-up,
FR←DP reverse flow [24-26]. In the case of nature’s
designs, the fundamental problem that exists in regard to
the above reverse engineering exercise is that of hydrating
naturesFR←DPhierarchiesinabottom-up sense. This is
because there is no explicit prior art that lends a helping
hand in the bottom-up structuring of the FR←DP
hierarchies. In this context, the suggestion in [25] to
consider the system evolution is of considerable
The first step is to study the previous systems in order
to identify system evolution.... The resources needed
to investigate system evolution are: standards,
patents, instruction for use, safety data sheets,
accident reports and other applicable resources
related to the system.
Using phylogenetic trees (for example, as created using
the highly conserved SSU rRNA, and discussed above),
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one may be able to trace the subtle additions and
subtractions between functioning organisms and their
respective genomes. The requisite bottom-up, hierarchical
mapping may be obtained by casting the overall
phylogenetic tree of life into a total FR←DP map ping.
Current genomic research is unaware of the axiomatic
design [27]. This is to be expected as the very concept of
design is looked down upon when considering nature’s
designs. Nevertheless, hydrating the genomic FR←DP
mapping in a bottom-up sense has significant and strategic
Consider, for example, the human genome project that
concluded in 2003:
The human genome has approximately 3.42 billion
nucleotides spread across 23 linear chromosomal
pairs in the nucleus.
Only 2% of the human genome codes for genes
(that number approximately 35,000) with
instructions for making proteins.
Rest 98% of the human genome (i.e., the non-
protein coding region) was considered as "junk
DNA", a term coined in 1972 by geneticist Susumu
Ohno [28].
the Information Axiom [16] which seeks to
minimize the information content in a design.
Firstly, the non-coding genome may be performing
the role of a ready-made inventory of body part
templates kept in reserve for a rainy day. These
may have been functional in the past, but are
silenced and non-functional in the current
environment [29].
Now consider the problem of regulating and
orchestrating the immense complexity of the
highly adaptable and dynamic genomic system.
Transposons or jumping genes were discovered in
the 1940s by the Nobel laureate and Maize
geneticist, Prof. Barbara McClintock. Transposons
were considered as part of junk DNA until 1965
when it was shown by Prof. McClintock that these
"junk DNA" elements had a regulatory role in
turning genes on and off. Transposons make up
more than 40% of the human genome [30]. And
like the SSU sRNA, transposons are highly
Regulatory structures create hierarchies as well as
heterarchic hierarchies. Transcription Factors
(TF’s) are proteins that attach to the DNA to
control the rate of DNA→RNA transcription.
There are close to 2600 TFs that regulate the
human genome. As Yu and Gerstein assert in [31]:
The relationships between TFs and their
target genes can be modeled in terms of
directed regulatory networks. These
relationships, in turn, can be readily
compared with commonplace ‘‘chain-of-
command’’ structures in social networks,
which have characteristic hierarchical
Reversing-Engineering the FR←DP mapping in the
genomic context involves reverse-engineering the design
trace that is embedded in the central dogma of molecular
to be done with meticulous care using tools from
disciplines such as complex adaptive systems, data-
sciences, bio-informatics, and phylogenetics. In all this,
the neglected Functional Domain needs to be kept center-
6. Conclusions
This is the very first foray into looking at naturally
occurring biological designs in the wild as an immense
creative laboratory that spans across geologically vast
temporal expanses. Conclusions, contributions as well as
shortcomings include:
i. Bottom-up stigmergic teleology is an original
proposition in this paper. It could help understand
designs in the biological realm without the need for
an agent-designer. Given the variety and the
immense quantity of biological artifacts available
for study, such designs could dramatically enrich
the theory of design.
ii. Despite the lack of an agent-designer, biological
designs do comport well with the axiomatic design
iii. A design-based approach to biology could aid as a
didactic tool in helping organize the vast
complexity of biological sciences.
iv. Bringing insights from axiomatic design-matrix
dynamics into the realm of biology, genomics, and
evolution could help articulate and capture the
hidden functions that are operative across various
biological scales (micro/meso/macro), including
that of the “junkDNA.”
v. The design principles of self-organization and self-
assembly that underlie biological morphogenesis
[32] have yet to be fully understood. The above
discussion fails to consider the “manufacturing
process” design of the biological artifact. Thus,
while the primary design map (FR↔DP) of the
flagellum complex has been considered, the equally
deserving, self-assembling DP↔PV mapping
(DNA↔RNA→Protein→Morphogenesis) needs
further research.
vi. It is impossible to capture the richness of the scale
and scope of biological designs in such a short
1. R. Dawkins. River Out of Eden: A Darwinian View
of Life. Basic Books. 1996.
2. C. Darwin. The Origin of Species: 150th
Anniversary Edition. Signet. 2003.
3. J. Thomas, A. Zaytseva. Mapping
Complexity/Human Knowledge as a Complex
Adaptive System. 2016 Wiley Periodicals, Inc., Vol.
21 No. S2. DOI 10.1002/cplx.21799. 24 June 2016.
MATEC Web of Conferences 301, 00023 (2019)
ICAD 2019
4. U. Wilensky. Ants. NetLogo Models Library.
5. P. P. Grassé. Insectes Sociaux VI. 79. 1959
6. J. H. Holland. Studying complex adaptive systems.
Journal of Systems Science and Complexity 2006,
19(1), 1-8.
7. H. Binswanger. The Biological Basis of
Teleological Concepts; ARI Press: Los Angeles,
8. J. Tabony. Microtubules viewed as molecular ant
colonies. Biology of the Cell 2006, 98, 603617, doi:
9. L. Sullivan. The Public Papers. University of
Chicago Press; 1 edition (April 14, 1988).
10. J. Thomas and P. Mantri, “Complex adaptive
blockchain governance,” in MATEC Web of
Conferences, vol. 223. EDP Sciences, 2018, p.
01010. https://www.matec-
11. Y. V. Morimoto, T Minamino Biomolecules (2014),
4, 217-234.
12. S. B. Guttenplan, K. M. Blair, D. B. Kearns 2010.
The EpsE flagellar clutch is bifunctional and
synergizes with EPS biosynthesis to promote
Bacillus subtilis biofilm formation. PLoS genetics,
6(12), e1001243. doi:10.1371/journal.pgen.1001243
13. Y. Nagata. Unlocking the secrets of nature's
nanomotor. Nikkei Asia Review. June 02, 2014.
14. "Flagellum" Wikipedia., n.p, Accessed
16 May 2019
15. "Type three secretion system" Wikipedia., n.p,
system Accessed 16 May 2019
16. N. P. Suh. The Principles of Design. 1st ed. New
York: Oxford University Press; 1990
17. T. Tashiro, A. Ishida, M. Hori, M. Igisu, M. Koike,
P. Méjean, N. Takahata, Y. Sano, T. Komiya. Early
trace of life from 3.95 Ga sedimentary rocks in
Labrador, Canada, Nature 549, 516518.
18. "Extinction event" Wikipedia., n.p,
Accessed 16 May 2019
19. B. Schmitz, K.A. Farley, S. Goderis, P.R. Heck,
S.M. Bergstrom, S. Boschi, P. Claeys,, V. Debaille,
A. Dronov, M. Ginneken, D.A.T. Harper, F. Iqbal, J.
Friberg, S. Liao, E. Martin, M.M.M. Meier, B.P.
Ehrenbrink, B. Soens, R. Wieler, F. Terfelt. An
extraterrestrial trigger for the mid-Ordovician ice
age: Dust from the breakup of the L-chondrite
parent body. Science Advances. September 2019.
Vol 5, no. 9. eaax4184.
20. B. L. Williams, E. D., JR. Brodie, E. D., III.
Coevolution of deadly toxins and predator
resistance: Self-assessment of resistance by garter
snakes leads to behavioral rejection of toxic newt
prey. Herpetologica 59:155163. 2003.
21. L. Pontieri. Discrimination behavior in the
supercolonial pharaoh ant. PhD Thesis. Centre for
Social Evolution. Department of Biology.
University of Copenhagen. June 2014.
22. M. Kimura. Neutral Theory Molecular Evolution.
Cambridge University Press. 1985.
23. S. O. Rogers. Integrated Molecular Evolution, 2nd
Edition. CRC Press. 2017
24. S. J. Lee, G. J. Park. A novel method of reverse
engineering using axiomatic design. Journal of
Mechanical Science and Technology 28 (2) (2014)
595~604. DOI 10.1007/s12206-013-1124-5.
25. L. Sadeghi, L. Mathieu, N. Tricot, L. Al-Bassit, R.
Ghemraoui. Toward Design for Safety Paet1:
Functional Reverse Engineering Driven by
Axiomatic Design. ICAD2013. The Seventh
International Conference on Axiomatic Design.
Worcester June 27-28, 2013
26. M. K. Thompson. Where is the 'Why' in Axiomatic
Design? ICAD2014. The Eighth International
Conference on Axiomatic Design. Campus de
Caparica September 24-26, 2014
27. D. J. Taxman (Editor). siRNA Design Methods and
Protocols. Springer. 2013.
28. M. L. Page. At least 75 per cent of our DNA really
is useless junk after all. New Scientist. 2017.
29. W. Makalowski. What is junk DNA, and what is it
worth? Scientific American. 2019.
30. L. Pray. Transposons, or Jumping Genes: Not Junk
DNA? Nature Education 1(1):32.
31. H. Yu, M. Gerstein. Genomic analysis of the
hierarchical structure of regulatory networks.
Proceedings of the National Academy of Sciences.
14724 14731, PNAS, October 3, 2006, vol. 103,
no. 40.
32. J. E. Fein. Possible Involvement of Bacterial
Autolytic Enzymes in Flagellar Morphogenesis.
Journal of Bacteriology. Vol 137. No. 2. Feb 1979.
p. 933-946.
MATEC Web of Conferences 301, 00023 (2019)
ICAD 2019
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